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This paper presents a method for indirect measurement of tire slip angles from chassis acceleration, yaw rate, and steer angle measurements. The chassis is assumed to be rigid so that acceleration data can be integrated to estimate velocities of the front and rear of the vehicle, from which slip angles can be predicted. The difference in front and rear slip angles is indicative of vehicle oversteer/understeer. Understeer data can then be correlated with position on the track to better understand vehicle handling behavior, aiding the tuning process. The technique is presented, and shown to work well with simulated data, even when the data is corrupted with up to 20% noise. Therefore, the inversion process presented here is theoretically sound. However, when the technique is applied to measured data from race cars, it is shown to be inaccurate. One suspected problem is the difficulty of getting accurate yaw rate data.

Operation & support costs for military weapon systems accounted for approximately 3/5th of the $500B Department of Defense budget in 2006. In an effort to ensure readiness and decrease these costs for ground vehicle fleets, health monitoring technologies are being developed for Condition-Based Maintenance of individual vehicles within a fleet. Dynamics-based health monitoring is used in this work because vibrations are a passive source of response data, which are global functions of the mechanical loading and properties of the vehicle. A common way of detecting faults in mechanical equipment, such as the suspension and chassis of a ground vehicle, is to compare measured operational vibrations to a reference (or healthy) signature to detect anomalies.

A methodology for modeling elastomeric mounts as nonlinear lumped parameter models is discussed. A key feature of this methodology is that it integrates dynamic test results under different conditions into the model. The first step is to model the mount as a linear model that is simple but reproduces accurately results from dynamic tests under small excitations. Frequency Response Functions (FRF) enables systematic calculation of the parameters for the model. Under more realistic excitation, the mount exhibits non-linearity, which is investigated in the next step. For nonlinear structures, a simple and intuitive method is to use time-domain force-displacement (F-x) curves. Experiments to obtain the F-x curves involve controlling the displacement excitation and measuring the induced forces. From the F-x curves, stiffness and damping parameters are obtained with an optimization technique.

Rolling element bearings provide near frictionless relative motion between two rotating parts. Automotive transmissions use various ball and rolling element bearings to accommodate the relative motion between rotating elements. In order to understand changes in bearing performance due to the loads imposed through the transmission, advanced modeling of the bearing is required. This paper focuses on the effects of cage flexibility on bearing performance. A flexible cage model was developed and incorporated into a six degree-of-freedom dynamic, deep groove ball bearing model. A lumped mass approach was used to represent the cage flexibility and was validated through an ANSYS forced response analyses of the cage. Results from the newly developed Flexible Cage Model (FCM) and an identical numerical model employing a rigid bearing cage were compared to determine the effects of varying ball-to-cage pocket clearance and cage stiffness on cage motion and ball-to-cage pocket contact forces.

Conventional suspension analysis of three-dimensional suspensions typically use two-dimensional analyses. This is done by projecting suspension components onto two-dimensional planes and then performing a two-dimensional analysis in each of these orthogonal planes or neglecting motions in one of the planes entirely. This requires multiple iterations because changes in one plane require a checking of their effects on motion in the other orthogonal planes. In doing so, much of the insight and accuracy gained from a three-dimensional analysis can be lost. A three-dimensional kinematic analysis approach is presented and applied to a dual A-Arm suspension system. All motions are considered instantaneously about a screw axis instead of a point as used by the usual two-dimensional modeling approach. The model predicts deflections of suspension components in response to the three-dimensional forces present at the contact patch.

Typical vehicle dynamics simulations demand a trade-off between short computation times and accuracy. Many of the more simple models are based on the kinematic roll center and the more accurate models tend to be multi-body dynamics simulation programs. There is a need for a model that improves the accuracy of the kinematic roll center models while still maintaining short computation times. Such a model could be used track-side during races to guide race teams toward improved handling. The model presented in this paper removes many of the assumptions and limitations of the kinematic roll center model. The model accounts for three-dimensional forces present at the contact patch and predicts deflections of suspension components. The modeling approach is applied to a NASCAR Craftsman Truck to predict the effects of suspension design and tuning on steady-state understeer characteristics of the vehicle. Braking and acceleration forces can also be applied to the vehicle.

This paper explains the basic principles behind two platform technologies that my research team has developed in the field of optical metrology and optical information processing: 1) high-speed 3D optical sensing; and 2) real-time 3D video compression and streaming. This paper will discuss how such platform technologies could benefit the automotive industry including in-situ quality control for additive manufacturing and autonomous vehicle systems. We will also discuss some of other applications that we have been working on such as crime scene capture in forensics.

Nested planetary gear trains, which consist of two integrated co-axial single-stage planetary gearsets, have recently been widely implemented in automobile transmissions and various other applications. In the current study, a non-destructive vibrational and acoustical monitoring technique is developed to detect a common type of gear grinding defect for a complex nested gear train structure. A nested gear train which has an unground pinion with unpolished teeth profile is used to exemplify the developed methodology. An experimental test stand with an open and vertical mounting configuration has been designed to acquire both vibrational and acoustical data. The measured data are investigated using several signal processing techniques to identify unground pinions in the gear system. A general frequency spectrum analysis is performed initially, which is then followed by a peak finding algorithm to identify the peaks in the spectrum.